An Overlap-based MILP Formulation for Task Allocation and Scheduling
Abhijit Davare, Jike Chong, Qi Zhu, Douglas Densmore, Alberto Sangiovanni-Vincentelli

Citation
Abhijit Davare, Jike Chong, Qi Zhu, Douglas Densmore, Alberto Sangiovanni-Vincentelli. "An Overlap-based MILP Formulation for Task Allocation and Scheduling". submitted, October, 2006.

Abstract
The deployment of applications on heterogeneous multi-core platforms is one of the most important challenges in the embedded systems design flow. In this paper, we develop an automated approach to tackle this problem that uses an efficient and extensible Mixed Integer Linear Programming (MILP) formulation. We show the effectiveness of our approach with extensive computational testing. For a case study involving the deployment of a Motion JPEG encoder application onto a Xilinx Virtex II Pro FPGA platform, we demonstrate that our automated approach can accurately capture the design space and yield systems that are competitive with manual designs.

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• HTML

  Abhijit Davare, Jike Chong, Qi Zhu, Douglas Densmore,
  Alberto Sangiovanni-Vincentelli. <a
  href="http://chess.eecs.berkeley.edu/pubs/119.html"
  >An Overlap-based MILP Formulation for Task Allocation
  and Scheduling</a>, submitted, October, 2006.

• Plain text

  Abhijit Davare, Jike Chong, Qi Zhu, Douglas Densmore,
  Alberto Sangiovanni-Vincentelli. "An Overlap-based MILP
  Formulation for Task Allocation and Scheduling".
  submitted, October, 2006.

• BibTeX

  @inproceedings{DavareChongZhuDensmoreSangiovanniVincentelli06_OverlapbasedMILPFormulationForTaskAllocationScheduling,
      author = {Abhijit Davare and Jike Chong and Qi Zhu and
                Douglas Densmore and Alberto
                Sangiovanni-Vincentelli},
      title = {An Overlap-based MILP Formulation for Task
                Allocation and Scheduling},
      booktitle = {submitted},
      month = {October},
      year = {2006},
      abstract = {The deployment of applications on heterogeneous
                multi-core platforms is one of the most important
                challenges in the embedded systems design flow. In
                this paper, we develop an automated approach to
                tackle this problem that uses an efficient and
                extensible Mixed Integer Linear Programming (MILP)
                formulation. We show the effectiveness of our
                approach with extensive computational testing. For
                a case study involving the deployment of a Motion
                JPEG encoder application onto a Xilinx Virtex II
                Pro FPGA platform, we demonstrate that our
                automated approach can accurately capture the
                design space and yield systems that are
                competitive with manual designs. },
      URL = {http://chess.eecs.berkeley.edu/pubs/119.html}
  }
  

Posted by Abhijit Davare on 15 May 2006.
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